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ngs-dna-umi-panel-variants

Run or plan targeted DNA panel variant workflows that use UMIs, duplex consensus reads, molecular barcodes, low-frequency calling, target coverage, and panel-specific QC.

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openai/plugins
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2026年6月3日 15:08
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SKILL.md
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name
ngs-dna-umi-panel-variants
description
Run or plan targeted DNA panel variant workflows that use UMIs, duplex consensus reads, molecular barcodes, low-frequency calling, target coverage, and panel-specific QC.
# UMI Panel DNA Variants Use this skill for targeted DNA panels where molecular barcodes, UMIs, duplex consensus, or low-frequency allele detection are central to the analysis. If the panel is ordinary germline calling without molecular consensus, use `ngs-dna-germline-variants`. ## Essential Inputs Confirm: - panel/capture kit name and target BED - UMI layout: inline read, index read, single UMI, duplex UMI, or unknown - whether consensus reads have already been generated - FASTQ/BAM input and pairing convention - reference build and panel-specific annotation requirements - minimum allele fraction goal and intended use: screening, research, validation, or exploratory - positive/negative controls and expected spike-ins when available ## Route Use a lab-validated panel workflow when provided. For public-tool planning, combine FASTQ QC, UMI extraction/consensus generation, alignment, target coverage QC, and variant calling as separate audited stages. Preflight command: ```bash python plugins/ngs-analysis/scripts/ngs_preflight.py --pipeline dna_umi_panel_variants --emit-install-plan ``` For compact local checks from prepared consensus or alignment BAM/CRAM files, use the dedicated UMI panel runner: ```bash python plugins/ngs-analysis/scripts/run_dna_umi_panel_variants.py \ --sample-sheet umi_panel_samples.tsv \ --reference-fasta reference.fa \ --target-bed panel_targets.bed \ --umi-mode duplex \ --umi-tag RX \ --execute ``` This writes the consensus/variant command plan, molecular-consensus state, low-frequency calling settings, visualization index, `qc/umi_postrun_summary.{tsv,json}`, `qc/umi_molecular_evidence_contract.{tsv,json}`, and consensus-BAM VCF outputs when the local fgbio/samtools/bcftools backend is available. The post-run summary parses consensus flagstat, target coverage, bcftools stats, and family-size/duplex files when present; missing metrics stay explicit in the notes column. The molecular evidence contract keeps the low-AF review requirements visible per sample: consensus BAM, family-size or molecule-support metrics, variant stats, hotspot review, and duplex review. The direct runner also emits `resources/resource_plan.json`, `resource_manifest.tsv`, `resource_env.sh`, and `resource_readiness.md`. The resource check is advisory by default so custom or reduced references can still be planned; add `--genome-build`, `--bundle-root <bundle>=<path>`, and `--require-resource-plan` when missing registered reference bundles should block readiness. ## Decision Points - Do not trim or discard UMI bases until their layout and destination are known. - Separate raw read depth from unique molecular depth and consensus depth. - Track on-target rate, coverage uniformity, family size distribution, strand/duplex support, and per-target dropout. - Low allele fraction calls require stronger artifact review than ordinary germline calls. - Use panel-specific hotspot/blacklist rules only when their provenance is known. ## Outputs Produce: - UMI layout and consensus strategy - target BED/resource manifest - raw-depth, molecular-depth, and consensus-depth QC summary - `qc/umi_postrun_summary.tsv` for consensus reads, target coverage, variant counts, family size, and duplex fraction - `qc/umi_molecular_evidence_contract.tsv` for low-AF evidence readiness, hotspot review, and duplex review expectations - variant calls with allele fraction, depth, strand/duplex support, and filtering rationale - limitations around sensitivity, panel dropout, molecule count, and non-validated interpretation
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